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10 articles for “driver fatigue”
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ADAS Implementation & Drowsiness Detection in Vehicle
Abstract: Driver fatigue is a leading cause of road accidents, especially in public and commercial transportation, posing serious risks to passenger and pedestrian safety. To address this critical safety issue effectively, this research study presents an AI-powered ADAS designed specifically for BS6-compliant buses, using real-time fatigue detection to prevent accidents. The system integrates a Raspberry Pi equipped with an AI Hat+ module to monitor driver drowsiness by detecting prolonged eye closures …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 1, 2026 · pp. 28–36 Read article
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An approach of Computer Vision Methods for Driver’s Drowsiness and Yawn Detection
Abstract: Numerous studies have demonstrated that 4,444 traffic crashes are primarily caused by driver drowsiness. Due to advancements in digital computer systems, tiredness behaviour may now be studied by researchers worldwide. The goal of this project is to increase road safety by preventing accidents caused by sleepy drivers. To view the driver's face, use real-time facial recognition technology. A driver's attentiveness and reaction time may be impacted by weariness, which raises …
Published in International Journal of Optical Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 21–26 Read article
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Driver Observation and Automatic Braking System Using Arduino
Abstract: Autonomous braking systems and driver observation are two important developments in car safety technology that are intended to reduce accidents brought on by tired drivers. An eye blink sensor has been incorporated in the device. The sensors recognize an eye blink automatically once the driver starts the engine. This gadget displays the sensor's output so that it may be compared to the Arduino. The eye blink sensor gets a signal …
Published in Journal of Microcontroller Engineering and Applications · Vol. 11, Issue 2, 2024 · pp. 28–33 Read article
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Driver Drowsiness Detection System
Abstract: One of the main causes of road accidents worldwide in recent years is driver fatigue. Assessing a driver's mood, or how sleepy they are, is a clear approach to gauge their level of exhaustion. Therefore, detecting driver fatigue is very important to save lives and property. The creation of a prototype drowsiness detection system is the aim of this research. The system operates in real time, continuously capturing images and …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 16–21 Read article
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Driver Anti-Sleep Alarming and Protection
Abstract: Road accidents due to driver drowsiness is one of the biggest problems worldwide, which kills thousands of people every year. Fatigue slows the reaction time, reduces the concentration, and, most importantly, impairs the judgment, thus making drowsy driving as dangerous as drunk driving. To reduce such accidents, various technologies have been employed to develop driver anti-sleep devices. These include sensor-based detection, camera-based eye monitoring, EEG analysis, and real-time alert systems. …
Published in International Journal of Electronics Automation · Vol. 4, Issue 1, 2026 Read article
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Driver Drowsiness Alert System
Abstract: In the present era, the increasing frequency of accidents during prolonged road trips, primarily attributed to driver fatigue, is a matter of serious concern. Recognizing this challenge, our goal is to develop a driver drowsiness alert system to effectively address and alleviate these incidents. Theproposed system utilizes a webcam to capture real-time images of the driver's eyes, employingmachine learning algorithms to promptly identify signs of fatigue. Upon detecting drowsiness, the …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 1, 2024 · pp. 1–10 Read article
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An IoT-Based Integrated Vehicle Safety System for Accident Detection and Driver Monitoring
Abstract: Driver fatigue, alcohol and slow response of emergency services are among a significant issue of road accidents. The paper will provide a real-life example of an IoT-based vehicle safety system, which will combine the accident detection, driver drowsiness and alcohol sensors with a cohesive system. The proposed system consists of use of accelerometer for sudden collision detection, infrared eye blink sensor for determining alertness of the driver and MQ-3 alcohol …
Published in International Journal of Electronics Automation · Vol. 4, Issue 2, 2026 Read article
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Development of Adaptive Cruise Control (ACC) and Lane Keeping Assist (LKA) Systems for Electric Vehicles
Abstract: This project investigates an IoT-power Adaptive Driver Assistance System (ADAS) crafted to enhance the comfort, efficiency, and reliability of Electric Vehicles (EVs). By seamlessly integrating Adaptive Cruise Control (ACC) and Lane Keeping Assist (LKA), the system aims to metamorphose driving into a secure, more comfortable, and energy-conscious experience using low-priced sensors and microcontrollers. The ACC module relies on ultrasonic sensing element linked to a NodeMCU, which intelligently corrects vehicle speed …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 1–6 Read article
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DRIVE-DEFENDER: A Driver Safety-oriented Alcohol and Drowsiness Detection System
Abstract: DRIVE-DEFENDER presents a pioneering approach in driver safety through the development of a real-time machine learning system for alcohol detection. The detrimental impact of alcohol-impaired driving on road safety necessitates efficient detection mechanisms. Current methodologies are often hindered by their cost, invasiveness, and reliance on specialized sensors. DRIVE-DEFENDER utilizes a camera for recording the face of the driver in real time, employing image processing techniques to identify facial landmarks. These …
Published in Journal of Open Source Developments · Vol. 11, Issue 1, 2024 · pp. 15–26 Read article
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Automatic Car Controller Based on Sign Board using Deep Learning and IOT
Abstract: The rapid growth of intelligent transportation systems has increased the demand for safer and more efficient driving solutions. Conventional vehicles often rely heavily on human intervention, which can lead to accidents due to negligence, fatigue, or poor visibility of traffic signs. This project proposes an automated car control system that utilizes deep learning and Internet of Things (IoT) technologies to recognize traffic signboards and respond accordingly. The primary objective is …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 2, 2026 Read article